Effective labor supply

Last registered on February 10, 2026
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Pre-Trial

Trial Information

General Information

Title
Effective labor supply
RCT ID
AEARCTR-0017600
Initial registration date
February 09, 2026

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
February 10, 2026, 6:46 AM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Name
Yoon Jo
Affiliation
Texas A&M University
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Other Primary Investigator(s)

PI Name
ChaeWon Baek
PI Affiliation
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PI Name
Vitaliia Yaremko
PI Affiliation
Contact Investigator

Additional Trial Information

Status
In development
Start date
2026-02-02
End date
2026-12-31
Keywords
Behavior
Additional Keywords
JEL code(s)
E31, C83, D84, J22, J24
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This project investigates how wage cuts affect workers’ labor supply decisions. Specifically, we study how different forms of wage cuts influence workers’ effective labor supply in an online labor market. By comparing workers’ responses across wage-cut environments, the project examines which margins of adjustment workers use when facing reductions in real wages and explores the mechanisms underlying these responses.
External Link(s)

Registration Citation

Citation
Baek, ChaeWon , Yoon Jo and Vitaliia Yaremko. 2026. "Effective labor supply ." AEA RCT Registry. February 10. https://doi.org/10.1257/rct.17600-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Participants complete short text transcription tasks over eight rounds in an online labor market. Compensation is held constant for the first two rounds to establish baseline performance.

Before the start of round 3, participants are randomly assigned to one of four remuneration schemes that vary nominal wages and prices, thereby generating nominal or real wage changes. Before the start of round 5, participants experience an additional wage adjustment of the same type as their initially assigned treatment. Before the start of round 7, participants experience a further wage adjustment consistent with their original assignment, and the compensation structure switches from a bulk-rate bonus to a piece-rate payment based on the number of tasks completed.
Intervention Start Date
2026-02-09
Intervention End Date
2026-12-31

Primary Outcomes

Primary Outcomes (end points)
The primary outcomes are measures of worker effort and effective labour supply across treatment arms, captured along multiple dimensions, including (i) take-up of additional work rounds, (ii) quantity of output produced, (iii) accuracy of output, and (iv) time taken to complete the task.

Primary Outcomes (explanation)
Work take-up: An indicator equal to one if the participant chooses to continue working in an additional round, capturing the extensive margin of labour supply.

Output quantity: The number of symbols correctly transcribed per round.

Accuracy (work quality): The share of correctly transcribed symbols or, equivalently, the number of transcription errors per round.

Quality-adjusted output: Output adjusted for transcription errors, reflecting effective productivity.

Time spent on task: The total time (in seconds) that a participant spends completing each task or round.

Productivity: The number of correctly transcribed symbols per unit of time spent on the task.

Secondary Outcomes

Secondary Outcomes (end points)
Self-reported reasons for changes in participation or effort are collected and analyzed as secondary outcomes to explore mechanisms underlying observed effort responses.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We conduct a randomized controlled experiment in an online labour market to identify the causal effects of real wage changes on worker effort. Participants complete a sequence of work tasks, with compensation held constant initially to establish baseline performance. Participants are then exposed to exogenous changes in compensation that generate nominal or real wage variation. Worker performance before and after compensation changes is compared across treatment groups.

Worker effort is measured along multiple dimensions, including participation, output, accuracy, and time spent on tasks. Comparing changes in these outcomes across treatment groups allows us to isolate the effect of real wage changes while holding task characteristics constant.
Experimental Design Details
Not available
Randomization Method
Randomization in the survey platform, qualtrics
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No cluster
Sample size: planned number of observations
8000 individuals
Sample size (or number of clusters) by treatment arms
2000 individuals per treatment arm = 8000 total
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Texas A&M University
IRB Approval Date
2025-07-01
IRB Approval Number
STUDY2025-0275
Analysis Plan